Senior Data Engineer

Senior Data Engineer

Location: 100% Remote (UK-based)

Employment Type: Permanent

Salary: Up to £75,000

Positions Available: 2

The Opportunity

We are looking for experienced Senior Data Engineers to play a key role in the evolution of a modern enterprise data platform built on Databricks and AWS.

This is an opportunity for highly autonomous engineers who enjoy ownership, solving complex data challenges, and contributing to scalable, high-quality data solutions in a cloud-first environment.

You’ll work across the full data engineering lifecycle, helping to design, build, optimise, and govern data products within a Databricks Lakehouse architecture.

Key Responsibilities

• Design, develop, and optimise scalable ETL/ELT pipelines using Databricks, Python, SQL, and Delta Live Tables (DLT).
• Build and maintain performant Delta Lake solutions, including partitioning and optimisation strategies.
• Contribute to Lakehouse architecture design and scalable ingestion frameworks.
• Develop governed, reusable, and maintainable data products.
• Implement data quality, observability, monitoring, and automated testing frameworks.
• Ensure alignment with governance, lineage, and security standards using Unity Catalog.
• Optimise Databricks cluster usage, orchestration, and cloud cost efficiency.
• Work collaboratively with architects, analysts, and stakeholders to translate business requirements into technical solutions.
• Mentor and support other engineers while contributing to engineering best practices and standards.
• Drive continuous improvement and innovation across the data platform.

Essential Skills & Experience

• Strong commercial experience as a Data Engineer or Senior Data Engineer.
• Deep hands-on expertise with Databricks on AWS (essential).
• Strong understanding of Spark, Delta Lake, and Lakehouse architectures.
• Proven experience designing scalable and maintainable modern data platforms.
• Strong knowledge of the end-to-end data engineering lifecycle.
• Experience with AWS cloud services in data engineering environments.
• Experience with Data Asset Bundles is highly desirable.
• Strong SQL and Python development skills.
• Understanding of data governance, metadata management, and quality frameworks.
• Ability to work autonomously and thrive in a self-directed environment.
• Strong communication and stakeholder management skills.

Ideal Candidate

The ideal candidate will be:

• A self-starter who enjoys autonomy and ownership.
• Comfortable operating in fast-moving engineering environments.
• Passionate about engineering quality, scalability, and continuous improvement.
• Confident influencing technical direction and best practice adoption.
• Delivery-focused with a pragmatic approach to solving problems.